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Popular backend title, mid-level 5-7 years band, and likely metro hiring increase applicant competition.
Specialized distributed-systems and data-lake expertise strongly limits cross-industry interchangeability.
Explicit 5-7 years requirement plus mandatory distributed-systems and big-data skillset enforces strict filtering.
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Provide technical leadership to design and implement scalable, high-performance services within a petabyte-scale distributed cloud file system.
Own complex feature design, architectural improvements, and engineering quality across the product lifecycle.
Mentor junior engineers and collaborate with product management and architects to deliver features with high quality and drive technical improvements.
5-7 years experience in building global scale distributed SaaS applications handling petabytes of data, preferably in a product company.
Strong programming skills in Go, Python, C, C++, or Java on Unix/Linux platforms.
Bachelor's or Master's degree in Computer Science or equivalent (B.E / M.E / M.Tech).
Hands-on experience with big data tools and frameworks (Datalake/Lakehouse, ETL), especially in AWS ecosystem including Apache Spark, AWS Glue, Iceberg.
Technically adept in complex systems design involving data consistency, scalability, OLAP data modeling, and query optimization at cloud scale.
Experienced in public cloud environments (AWS) with deep understanding of distributed storage, eventual consistency, and big data pipelines.
Capable of independently guiding teams, handling engineering escalations, and advancing product architecture while integrating emerging technologies like generative AI tools in software development.